A Study of the Performance of Actively-Managed Funds in Asia-Pacific Market

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Three scenarios were examined, and each scenario had specific criteria of sample selection. The first scenario compared the fund performance between those investing in emerging market and developed market. The funds we selected were equity funds with international investment scope. Within each market, we conducted situation analysis, which will be elaborated in Section 3.2, and compared the performance. The second scenario was about the fund performance in upward and downward economy. We used Hang Seng Index as an indicator of the economy status and set a 7-year time span from April 2006 to June 2013 covering the 2008 financial crisis as well as the subsequent economic recovery. Several booming/recession periods were combined in order to expand the investigation horizon. In the third scenario, we closely examined sample funds within industry sectors. The market research showed that Real Estate and Information Technology sectors were the two largest ones in the Asian fund market. Therefore, we focused on those two industries to better serve the general investors’ preference. In each scenario, we first selected all the qualified funds, and then randomly sampled within the population in order to avoid data biases and make the result more representative.

3.2 Models and Data Processing

To better analyze the risk-return tradeoff of actively managed funds under the three scenarios, we used the Capital Asset Pricing Model (CAPM), non-linear model (market timing), and the Fama-French three-factor model to adjust the risks. Regarding the data selection of risk free rate, the HK10-year Exchange Fund Note yield of the selected period was used for the second scenario, and LIBOR was used for the first and third scenarios considering the global exposure of selected funds. Based on the coverage and index construction, benchmark indices with the most matching coverage and reliable calculation were carefully selected for each scenario. We picked MSCI Emerging Markets Index and Vanguard FTSE Developed World Index for emerging market and developed market, respectively. Hang Seng Index was chosen for the second scenario. In the third scenario, which is the sector analysis, we chose Hang Seng REIT Index for Real Estate sector and Hang Seng Composite Index of Information Technology for IT Sector. We cleared up the data and only used the monthly returns to eliminate noises due to daily firm-specific fluctuation.

The CAPM firstly separates the β risk and the abnormal profit (α) of the funds selected. It indicates how sensitive the fund is to the market movement, and whether managers could capture abnormal returns. In particular, we obtained the monthly returns of the selected funds from Bloomberg and performed regression analysis for each fund between its excessive return (Rp-Rf) and the market risk premium (Rm-Rf). Then, t-test and r2 test was also conducted for each regression equation to test the significance of the factor. The α measures the difference between the equilibrium return and the actually expected return, which we interpreted as the risk-adjusted return realized by managers. The positive α represents the abnormal return captured by fund managers and reflects the level of market inefficiency. With a significantly positive α and β closed to 1, we could postulate that the fund manager has exceptional portfolio management skills to generate extra return and at the same time keep up with the market return.

Then the non-linear regression model was implemented to further decompose the profit arisen in management skills from the total excess return. We ran a non-linear regression of (Rp-Rf) against both (Rm-Rf) and (Rm-Rf)2. Then, if the return of actively managed fund is found to be highly correlated with the squared term (Rm-Rf)2, then it is reasonable to conclude that the fund manager has successfully timed the market by increasing the β risk of its portfolio in bullish markets and decreasing its β risk in bearish markets. Basically, the active management return is derived from market timing and security selection. In our research, we mainly focus on more general level of asset allocation, and such non-linear relationship would be another indicator for effective active management.

Lastly, Fama-French model was adopted in order to account for the difference in firm size and book-to-price ratio. We retrieved SMB and HML statistics from the Fama-French database based on the assumption that the two factors are globally representative. With monthly SMB, HML, and market risk premium (Rm-Rf) on hand, we ran a second set of regressions with three independent variables. The intercept of the new regressions, which we denoted as (α’), measured the performance of fund managers after adjustment for firm size and book-to-price ratio differences, and it is considered to be a better indicator of fund managers’ skills.

In summary, the CAPM was the starting point of our performance evaluation and provided us a general picture of the excess return attributed to managers’ skills and systematic risk. Then we further adjusted the fund return based on management specific factors (using the non-linear market timing model) and risk factors (using the Fama-French Three-Factor Model). The results would indicate the level of active fund management, under the characteristics of certain market conditions or sectors, and the degree of market efficiency.

4. Analysis of Results

Applying the methodology above, we expected to derive results on the performance of actively managed funds compared to benchmark index under different market structures, economic status and market sectors.

4.1 Scenario 1: Emerging Market vs. Developed Market

Ten equity funds with international investment focus are selected, and the investment targets of those funds are emerging markets securities. In all three models, MSCI Emerging Markets Index is selected as a benchmark because of its representativeness and wide coverage. The MSCI Emerging Markets Index contains more than 800 securities across 21 emerging markets.

For developed market, we also chose ten equity funds with international investment focus. As for index selection, in order to maintain the sample size, the benchmark index should incept at least before year of 2010. Some representative indexes, such as MSCI developed world index, BlackRock developed world index, FTSE developed index and S&P developed index, are exclusive because they incepted later than 2010. Considering inception date, Vanguard FTSE Developed World ex UK Equity Index Fund is selected as our benchmark index. Since UK equities are excluded in the composition of the index, we will correspondingly avoid choosing